Internal quality assurance practices of nursing and midwifery training colleges and the role of regulatory bodies: The perspectives of health tutors
Bibliographic record
Abstract
In the era of quality orientation, human rights, and a consumer-driven society, Nursing and Midwifery Education Institutions (NMEI) are expected to produce qualified graduates who will meet the needs and expectations of society. The aim of the study was to assess the internal quality assurance practices of Nursing and Midwifery Training Colleges (NMTCs) in the Northern Region of Ghana. An analytical cross-sectional design was adopted for the study with a sample size of eighty-eight (88). Purposive sampling method was used to select health tutors (participants) from three NMTCs in the Northern Region of Ghana. Data for the study were collected with a questionnaire and analysed. The study revealed that the NMTCs have quality assurance units/committees responsible for monitoring the quality of teaching and learning. In this study, only 39.8% of the health tutors were satisfied with the monitoring and inspection of training institutions by regulatory bodies. The results show a significant difference among the perspectives of the health tutors on the implementation of staff professional development (F(2, 87) = 4.74, p = .011), academic staffs motivation in the direction of refining the value of academic programs (F(2, 87) = 3.43, p = .037), working conditions of staffs (F(2, 87) = 3.32, p = .041) and the effectiveness of quality assurance systems in enhancing the quality of teaching and assessment (F(2, 87) = 3.27, p = .043). There is the need to ensure uniformity in staff professional development, working conditions, and motivation of health tutors in the training institutions. Regulatory bodies must intensify the monitoring of NMTCs and offer accreditation to new NMTCs based on the state of educational resources and facilities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".